Consider this scenario. Two 60-year old women live 10 miles apart in the Washington DC area. They’ve both been prescribed beta-blockers for high blood pressure, both have family histories of Type 2 diabetes, and have missed their last few annual check-ups. What should their care plans look like? Should they be different?
Clinically, they’re spitting images of each other. However, one piece of data — their zip code — can dramatically tilt the equation. Turns out, they face radically different life expectancies (63 versus 96 years), just based on the difference in their geographic locations. This 33-year life expectancy gap can be chalked up to differences in income level, education level, and access to grocery stores with fresh food.
A hospital EHR system can tell the full story of a patient’s care, and we’ve built advanced tools to make sense of it all: clinical decision-making aids, population health segmentation tools, and automated billing and coding assistants.
However, the never-ending quest to create clinical data models belies one fatal fallacy: clinical data doesn’t tell the whole story.
Prescribing the right dosage of blood pressure meds doesn’t matter if a patient can’t understand the label. Monitoring glucose levels isn’t helpful if the only sources of food are corner stores and fast-food joints. Appointment reminders are meaningless if it takes two hours and three bus transfers to get to the clinic.
These factors determine 80% of a patient’s overall health. The best evidence-based care plans won’t work if we can’t get the patient to the starting line. And this is a reality that existed before we ever even heard of Covid-19.
Engaging, Connecting, and Communicating is the Critical First Step
The solution to leveling the healthcare playing field for everyone is not an easy one. The investments required will be massive and take time. But the widespread recognition of the seriousness of the problem and making it a priority presents some degree of newfound hope.
Ultimately, technology innovation will need to be at the center of the next generation of healthcare, and it must work for everybody. The industry has been slowly innovating for decades, but the pandemic forced a new level of urgency and ultimately proved that virtual care does work, it is more efficient, and patients enjoy it.
The Achilles heel of healthcare innovation has never been a lack of functionality. There is a lot of robust, powerful IT out there. The problem is that not enough patients are using digital tools because most of the technology has been inaccessible, or too “dense” and complex for most people to use.
Even though over 80% of U.S. adults own smartphones, patient adoption rates of healthcare apps still hover in the 10% range. Great apps alone are not enough, and healthcare IT designers have massively overestimated what consumers are willing to put up with.
To overcome the adoption friction, a new class of mobile technology is emerging that uses conversational AI to engage patients. Rather than requiring downloads, usernames, passwords, and complex menu trees, users simply communicate through smart messaging on their smartphones. Language is the user interface.
We are now seeing examples where patient engagement rates with conversational chatbots are 80%, workflow completion rates are 95%, and satisfaction rates are more than 90%. Banner Health is rolling out virtual waiting rooms to replace the physical spaces that patients don’t value and handling all the pre-appointment check-in through conversational digital assistants. Each year, hundreds of thousands of patients in the Banner network bypass the waiting room when seeing their doctors. Healthcare is changing.
Digital Assistants Going into Disadvantaged Communities, Helping People Where They Are
As healthcare virtualizes and removes barriers to high-volume, high satisfaction digital engagement, the opportunity to tune and leverage those solutions in disadvantaged communities becomes more doable than ever before. Today’s mobile technology can reach out and engage a much broader population. Patients no longer need a PC, or an email account, or high-speed internet. They just need a smartphone.
It’s no longer correct to assume that individuals from underserved communities lack access to modern digital tools. Many assumptions have been debunked and the reality is most people have smartphones, including people in underserved, Medicaid populations.
If the goal is to improve access and engage underserved communities where smartphone penetration is more than 80%, the path forward is mobile. At the same time, advanced conversational AI is breaking down complexity barriers and driving better engagement.
So much can be accomplished virtually with patients through their smartphones. With conversational AI, the ability to connect and guide patients through countless, often difficult administrative tasks from the comfort of their bedroom remove a key engagement hurdle. The digital assistant can also check-in, follow up, recommend, and educate in the language, voice, or personality of the patient’s choosing. And it can all be done from the comfort of a home, or even a bus.
Importantly, these digital experiences don’t require an army of human teams to execute. The interactions are automated and designed to run at scale across all patient populations. Digital assistants don’t replace vital person-to-person interactions, they simply augment human teams by taking care of the redundant, time-consuming, often complex tasks so the care team interactions can focus on what’s important — the patient’s health.
Good software code alone will not overcome the array of healthcare challenges that people living in the wrong zip code face. But good, smart communications is a fundamental starting point and conversational AI has matured enough to start leveling the playing field.